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Purpose – The purpose of this study is to explore the concept of the economic lot sizing and the time cycle period of reordering. The stochastic demand is quite common in the real environment of a cement retailer. The study compares three methods to obtain the optimal solution of a lot-sizing ordering from the real case of the previous study where the dataset is collected from the area of some retailers at Banda Aceh Province of Indonesia.

Design/Methodology/Approach – The problem model appears when the retailer with shortage has to fulfill the lot size in the optimal condition to the stochastic demand while at the same time has the backlog condition. Moreover, when the backorder needs the time horizon for replenishment where this condition influences the holding cost at the store, many retailers try to solve this problem to minimize the holding cost, but on the other side, it should fulfill the customer demand. Three methods are explored to identify that condition: a Wagner–Whitin algorithm, the Silver–Meal heuristic, and the holding and ordering costs. The three methods are applied to the lot sizing when there is a backlog.

Findings – The results of this study show that the Wagner–Whitin algorithm outperforms the other two methods. It shows that the performance increases around 27% when compared to the two other methods in this study.

Research Limitations/Implications – All models are almost approximate and useful to determine the cycle period on stochastic demand.

Practical Implications – The calculation of the dataset with the three methods would give the simple example to the retailer when he faces the uncertainty demand models. The prediction of the calculation is done accurately than the constant calculation, which is more economic.

Social Implications – The calculation will contribute to much better predictions in many cases of uncertainty.

Originality/Value – This is a initial comparative model among other methods to achieve the optimal stock and order for a retailer

Purpose – The purpose of this study is to develop a numerical framework to predict the time-dependent probability of failure of a bridge subjected to multiple vehicle impacts. Specially, this study focuses on investigating the inter-relationship between changes in life-cycle parameters (e.g., damage size caused by vehicle impact, loss of initial structural capacity, and threshold intervention) and bridges probability of failure.

Design/Methodology/Approach – The numerical procedure using MATLAB program is developed to compute the probability failure of a bridge. First, the importance and characteristics of life-cycle analysis is described. Then, model for damage accumulation and life cycle as a result of heavy vehicle impacts is discussed. Finally, the probability of failure of a bridge subjected to vehicle impacts as a result of change in life-cycle parameters is presented.

Findings – The results of study show that damage size caused by both vehicle impacts and loss of initial structural capacity have a great impact on the long-term safety of bridges. In addition, the probability of failure of a bridge under different threshold limits indicates that the structural intervention (e.g., repair or maintenance) should be undertaken to extend the service life of a bridge.

Research Limitations/Implications – The damage sizes caused by heavy vehicle impacts are based on simple assumptions. It is suggested that there would be a further study to estimate the magnitude of bridge damage as a result of vehicle impact using the full-scale impact test or computational simulation.

Practical Implications – This will allow much better predictions for residual life of bridges which could potentially be used to support decisions on health and maintenance of bridges.

Originality/Value – The life-cycle performance for assessing the time-dependent probability of failure of bridges subjected to multiple vehicle impact has not been fully discussed so far.

Purpose – This purpose of the research is to investigate the process of manufacturing LDPE recycle thermoplastic composites with reinforcement oil palm empty fruit bunch (OPEFB) biomass microfillers.

Design/Methodology/Approach – Methods of physical and chemical modification of OPEFB fibers into the LDPE matrix and the addition of some compatibilizer such as MAPE and xylene process through melt blending can improve mechanical properties, electrical properties, biodegradability, and improve the morphology of composites.

Research Limitations/Implications – These composites are prepared by the following matrix ratio: filler (70:30)% and filler size (63, 75, 90, and 106) μm. The LDPE plastic is crushed to a size of 0.5–1 cm, then pressed with hot press free heating for 5 min and with a pressure of 10 min at 145 °C. Based on the characterization obtained, the tensile strength and the high impact on the use of 106 μm filler is 13.86 MPa and 3,542.6 J/m², and thermal stability indicates the degradation temperature (T₀) 497.83 °C. FT-IR analysis shows the presence of functional groups of cellulose and lignin molecules derived from TKKS collected in the composite.

Practical Implications – Based on the characterization obtained, this composite can be applied as furniture material and vehicle dashboard.

Originality/Value – Composites obtained from recycle of LDPPE plastics waste has some advantages such as good compatibility and high tensile strength. This composite used the OPEFB filler whose size is in micrometer, and so this product is different from other products.

Work-life flexibility policies (e.g., flextime, telework, part-time, right-to-disconnect, and leaves) are increasingly important to employers as productivity and well-being strategies. However, policies have not lived up to their potential. In this chapter, the authors argue for increased research attention to implementation and work-life intersectionality considerations influencing effectiveness. Drawing on a typology that conceptualizes flexibility policies as offering employees control across five dimensions of the work role boundary (temporal, spatial, size, permeability, and continuity), the authors develop a model identifying the multilevel moderators and mechanisms of boundary control shaping relationships between using flexibility and work and home performance. Next, the authors review this model with an intersectional lens. The authors direct scholars’ attention to growing workforce diversity and increased variation in flexibility policy experiences, particularly for individuals with higher work-life intersectionality, which is defined as having multiple intersecting identities (e.g., gender, caregiving, and race), that are stigmatized, and link to having less access to and/or benefits from societal resources to support managing the work-life interface in a social context. Such an intersectional focus would address the important need to shift work-life and flexibility research from variable to person-centered approaches. The authors identify six research considerations on work-life intersectionality in order to illuminate how traditionally assumed work-life relationships need to be revisited to address growing variation in: access, needs, and preferences for work-life flexibility; work and nonwork experiences; and benefits from using flexibility policies. The authors hope that this chapter will spur a conversation on how the work-life interface and flexibility policy processes and outcomes may increasingly differ for individuals with higher work-life intersectionality compared to those with lower work-life intersectionality in the context of organizational and social systems that may perpetuate growing work-life and job inequality.

Purpose – This study aims to analyze and assess the relation of freight transportation for regional development in the north zone of Aceh. The impact of freight transportation to accelerate the delivery of goods as observed through several indicators including regulation, retribution, freight entrepreneur, trucker, size of truck bin, punctuality, loading and unloading systems on regional planning supporting has been focus of this study.

Design/Methodology/Approach – The freight transportation in north zone of Aceh, covering Lhokseumawe, Aceh Utara, Bireuen, BenerMeriah and Aceh Tengah regencies will be examined. In several indicators including regulation, retribution, freight entrepreneur, trucker, size of truck bin, punctuality, loading and unloading systems the freight transportation will be surveyed for the analysis. The factors which contribute in the development of the area through freight transportation are the economic growth, human resources improvement, management of land use and environmental harmonization. This regional development approach aims to determine a connection between the two variables.

Findings – The results of the study show that variables of freight transportation in several indicators including regulation, retribution, freight entrepreneur, trucker, size of truck bin, punctuality, loading and unloading systems have a significant impact on regional development. It is indicated by the value of 0.214 in the regression weight result.

Research Limitations/Implications – This research has implications on the relation of freight transportation with regard to several indicators including regulation, retribution, freight entrepreneur, trucker, size of truck bin, punctuality, loading and unloading systems on the regional development based on the aspect of economic growth, human resources improvement, management of land use and environmental harmonization.

Practical Implications – The result of this study will be an important input to the Aceh government, county and city governments in the north zone in Aceh to encourage the establishment of a road network to accelerate freight transportation in that region for the development of new economic zones.

Originality/Value – This study suggests that freight transportation has the strongest links to significantly influence the activities of regional development, so it can be recommended for the Aceh government, county and city governments in the north zone of Aceh to orient road network policy towards the development of the new economic area and support the implementation of the special economic zones of Arun, Lhokseumawe.

Since its introduction by Chari, Kehoe, and McGrattan (2007), Business Cycle Accounting (BCA) exercises have become widespread. Much attention has been devoted to the results of such exercises and to methodological departures from the baseline methodology. Little attention has been paid to identification issues within these classes of models. In this chapter, the authors investigate whether such issues are of concern in the original methodology and in an extension proposed by Šustek (2011) called Monetary Business Cycle Accounting. The authors resort to two types of identification tests in population. One concerns strict identification as theorized by Komunjer and Ng (2011) while the other deals both with strict and weak identification as in Iskrev (2010). Most importantly, the authors explore the extent to which these weak identification problems affect the main economic takeaways and find that the identification deficiencies are not relevant for the standard BCA model. Finally, the authors compute some statistics of interest to practitioners of the BCA methodology.

Purpose – The purpose of the research aims to observe the high growth of corn crops with a different cropping pattern.

Design/Methodology/Approach – The research is conducted based on field experiments with Group Randomized Design (hereafter RAK shortened from Cluster Random Design). The treatment of cropping pattern I is that corn crops are planted in one row with the size of plot 9 m × 4 m, and the distance planting of the crops is 70 cm × 40 cm. Cropping pattern II is that corn crops are planted in two rows with the size of plot 9 m × 4 m, and the distance planting is 70 cm × 40 cm. Cropping pattern III is that corn crops are planted in three rows with the size of plot 9 m × 4 m, and the distance among the crops is 70 cm × 40 cm.

Findings – The result of research shows that the highest corn crops are from cropping pattern II.3 at age 15 and 30 after planting time (called HariSetelahTanam or HST). The increase of cropping rows from one row to two rows indicates that intra-specific competition are more dominant. The growth of crops is faster because they need full sunlight at vegetative and generative stages. The need of full sunlight at the growing stage causes the increasing of stem height of crops to enable the crops to receive the sunlight optimally due to the continuity of photosynthesis process. The increasing growth of stem diameter is in accordance with the growth speed of height plant at the same age.

Research Limitations/Implications – This research intends to find out the best growing process of the plant. Further research is needed to study the outcome of final product of the plant.

Practical Implications – This is to see the utilization of the best cropping pattern and optimal land utilization.

Originality/Value – High growth of corn crops and stem diameter (Zea may, S) with a different cropping pattern has not yet been published.

Purpose: Previous research identified a measurement gap in the individual assessment of social misconduct in the workplace related to gender. This gap implies that women respond to comparable self-reported acts of bullying or sexual discrimination slightly more often than men with the self-labeling as “bullied” or “sexually discriminated and/or harassed.” This study tests this hypothesis for women and men in the scientific workplace and explores patterns of gender-related differences in self-reporting behavior.

Basic design: The hypotheses on the connection between gender and the threshold for self-labeling as having been bullied or sexually discriminated against were tested based on a sample from a large German research organization. The sample includes 5,831 responses on bullying and 6,987 on sexual discrimination (coverage of 24.5 resp. 29.4 percentage of all employees). Due to a large number of cases and the associated high statistical power, this sample for the first time allows a detailed analysis of the “gender-related measurement gap.” The research questions formulated in this study were addressed using two hierarchical regression models to predict the mean values of persons who self-labeled as having been bullied or sexually discriminated against. The status of the respondents as scientific or non-scientific employees was included as a control variable.

Results: According to a self-labeling approach, women reported both bullying and sexual discrimination more frequently. This difference between women and men disappeared for sexual discrimination when, in addition to the gender of a person, self-reported behavioral items were considered in the prediction of self-labeling. For bullying, the difference between the two genders remained even in this extended prediction. No statistically significant relationship was found between the frequency of self-reported items and the effect size of their interaction with gender for either bullying or sexual discrimination. When comparing bullying and sexual discrimination, it should be emphasized that, on average, women report experiencing a larger number of different behavioral items than men.

Interpretation and relevance: The results of the study support the current state of research. However, they also show how volatile the measurement instruments for bullying and sexual discrimination are. For example, the gender-related measurement gap is considerably influenced by single items in the Negative Acts Questionnaire and Sexual Experience Questionnaire. The results suggest that women are generally more likely than men to report having experienced bullying and sexual discrimination. While an unexplained “gender gap” in the understanding of bullying was found for bullying, this was not the case for sexual discrimination.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.